Analyzing MOOC discussion forum messages to identify cognitive learning information exchanges

Wong, Jian-Syuan; Pursel, Bart; Divinsky, Anna; Jansen, Bernard J.

doi:10.1002/pra2.2015.145052010023

Cited by 22 publications

(9 citation statements)

References 24 publications

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“…PSU and UCM have had a greater research focus on education data mining and visualization. For example, Wong et al ( 2015 ) from PSU used a keyword taxonomy approach to analyze large quantities of MOOC forum data and identify the types of learning interactions taking place in forum conversations, and Moreno-Marcos et al ( 2018 ) from the UCM analyzed the predictive power for anticipating assignment grades in a MOOC. MOOC research from MIT, HU, the OU of the Netherlands, and AU has mainly focused on the demographic features of MOOC learners.…”

Section: Discussionmentioning

confidence: 99%

A bibliometric review on latent topics and trends of the empirical MOOC literature (2008–2019)

Liu

Zou

Chen

et al. 2021

Asia Pacific Educ. Rev.

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Massive Open Online Courses (MOOCs) have become a popular learning mode in recent years, especially since the outbreak of COVID-19 in late 2019, which had resulted in a significant increase in associated research. This paper presents a bibliometric review of 1078 peer-reviewed MOOC studies between 2008 and 2019. These papers are extracted from three influential databases, the Web of Science (WOS), Scopus, and the Education Resources Information Center (ERIC). The MOOC literature analysis with a bibliometric approach identified the research trends, journals, countries/regions, and institutions with high H-index, scientific collaborations, research topics, topic distributions of the prolific countries/regions and institutions, and annual topic distributions, after which the representative research and research implications were discussed. This review gives researchers a deep and comprehensive understanding of current MOOC research and identifies potential research topics and collaborative partners, which supports MOOC-related future research.

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Section: Discussionmentioning

confidence: 99%

A bibliometric review on latent topics and trends of the empirical MOOC literature (2008–2019)

Liu

Zou

Chen

et al. 2021

Asia Pacific Educ. Rev.

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“…A text mining approach to constructing a domain ontology for representing the educational domain is proposed in [24]. The purpose of the domain model is to help students in making the choice of their desirable concepts.…”

Section: Related Workmentioning

confidence: 99%

Mining the Students’ Chat Conversations in a Personalized e-Learning Environment

Al-Abri

Al-Khanjari

Jamoussi

et al. 2019

Int. J. Emerg. Technol. Learn.

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Providing personalized e-learning environment is normally relying on a domain model representing the knowledge to be acquired by learners and learners’ characteristics to be used in the personalization process. Therefore, constructing the domain model and understanding the characteristics of the learners are very crucial in such an environment. With the inclusion of social collaboration tools for collaborative learning activities, the generated data during conversations enrich with valuable information to be used for personalization. However, when considering chat conversations as a source for constructing the domain model, there is a need to perform a mining technique for chat conversations in order to extract the semantic relations from the user-generated contents hidden inside these conversations. As well as the learner’s characteristics like learning style and knowledge level expressed during conversations. Thus in this paper, we are aiming for the best utilization of chat conversation by proposing a model containing a rule-based technique as a form of mining technique. This mining aims at extracting the semantic relations to build the domain model as an ontology-based depiction. In addition, the mining model is proposed to perform some collaborative filtering techniques to identify the learning styles and knowledge level of the learners.

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“…Other studies of this type propose systems for seeking events of the users as a means of management (Wong, Pursel, Divinsky, & Jansen, 2015). In this proposal, the system uses a keyword taxonomy approach in order to analyze a vast amount of MOOC forum data with the goal of identifying types of learning interactions and relations occurring in the forums.…”

Section: Related Work About Moocs and Odl Managementmentioning

confidence: 99%

A Computational Method for Enabling Teaching-Learning Process in Huge Online Courses and Communities

Mora

Ferrández

Gil

et al. 2017

IRRODL

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Massive Open Online Courses and e-learning represent the future of the teaching-learning processes through the development of Information and Communication Technologies. They are the response to the new education needs of society. However, this future also presents many challenges such as the processing of online forums when a huge number of messages are generated. These forums provide an excellent platform for learning and connecting students of the subject, but the difficulties in following and searching the vast volume of information that they generate may produce the opposite effect. In this paper, we propose a computational method for enabling the educational process in huge online learning communities. This method analyses the forum information through Natural Language Processing techniques and extract the main topics discussed. The results generated improves the management of the forums, increases the effectiveness of the teachers' explanations and reduces the time spent by students to follow the course. The proposal has been complemented with a real case study that shows promising results.Keywords: natural language processing, topic detection, distance learning, online forum, mooc managing, However, there are still challenges that should be specifically addressed in order to achieve the effective ODL provision and to maintain excellent educational standards. One of the most powerful and popular tools are online forums (Mora, Signes Pont, DeMiguel Casado, & Gilart Iglesias, 2015). Online forums are a communication technology tool in education and provide an excellent platform for learning and connecting students to the subject. The expected roles of the forums are to increase engagement of students in the subject, promote deep learning, and maintain motivation (Onah et al., 2014).Technological advances and computing methods may provide tools for enhancing these roles and facilitating the educational process. In this way, artificial intelligence approaches based on NaturalLanguage Processing (NLP) should deliver tools specifically aimed at students and teachers to make the assimilation of content and course tracking easier for students, and to provide mechanisms to manage the learning platforms by teachers. The working hypothesis of our research is that this kind of solution can be used to better engage the students and teachers in online platforms with huge forums by enabling the knowledge management and learning-teaching processes. Under our approach, the main objective of our work is to provide automatic tools and applications to facilitate tracking and monitoring online learning communities through the automatic processing of forums of lexical, syntactic, and semantic analysis; clustering; and information retrieval techniques. A Computational Method for Enabling Teaching-Learning Process in Huge Online Courses and Communities Mora, Ferrández, Gil, and Peral 227The remainder of the paper is structured as follows: Section 2 describes the problem of management and monitoring forums in huge online ...

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Analyzing MOOC discussion forum messages to identify cognitive learning information exchanges

Cited by 22 publications

References 24 publications

A bibliometric review on latent topics and trends of the empirical MOOC literature (2008–2019)

A bibliometric review on latent topics and trends of the empirical MOOC literature (2008–2019)

Mining the Students’ Chat Conversations in a Personalized e-Learning Environment

A Computational Method for Enabling Teaching-Learning Process in Huge Online Courses and Communities

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